Evolve with vellum-assistant
Control Vellum Assistant to get a personal AI that adapts with you over time.
Create automations that proactively reach out and adapt to your needs, like sending welcome emails to new customers.
With Vellum Assistant, you can focus on more important tasks without the need for manual updates or repetitive workflows.
"A founder, Sarah, uses Vellum Assistant to keep track of her startup's progress, getting personalized updates on key metrics like user growth and revenue. She connects it to her Slack channel to receive proactive updates and insights. By using Vellum Assistant, Sarah saves time and stays on top of her business without needing a full-time assistant."
Beginners can try this out to get a feel for personal AI assistants and how they can fit into daily workflows.
Senior engineers and professionals might reach for Vellum Assistant to explore AI-powered automation and integration opportunities.
Note that Vellum Assistant requires some configuration and setup, but it can adapt and learn over time to provide more personalized support.
Vellum-assistant provides a personal AI companion with memory and personality that can be accessed across macOS, Telegram, and Slack, evolving with the user over time.
git clone https://github.com/vellum-ai/vellum-assistant.git- β’When you need a consistent AI assistant that remembers previous conversations and adapts to your preferences
- β’When integrating AI capabilities into your workflow across multiple platforms (macOS, Telegram, Slack) is necessary
- β’When a proactive AI reach-out feature is required for tasks or reminders
- 1Run 'npm install' in the cloned repository to set up the project
- 2Configure the 'vellum.config.json' file to specify your preferred AI personality and memory settings
- 3Start the assistant with 'npm start' and follow the setup instructions for macOS, Telegram, or Slack integration
- 4Test the assistant's memory by asking it to recall previous conversations or tasks
- 5Customize the assistant's personality by adjusting the configuration options in 'vellum.config.json'
Ask the Vellum assistant 'What were our last three discussions about?' to demonstrate its memory feature
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